Pharmacogenetic Optimization of Analgesic Prescribing in Sickle Cell Disease

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DESCRIPTION (provided by applicant): This proposal describes a three year mentored training program for Dr. Cheedy Jaja to create a robust foundation in sickle cell disease (SCD) pharmacotherapy and analgesic pharmacogenetics essential for his transition to an independent translational research scientist with expertise in SCD pain management. A customized program of study that couples didactic coursework and research training with clinical and laboratory training in SCD pathophysiology, pain management and pharmacogenetics is designed. Dr. Abdullah Kutlar, a leading authority in SCD pain management will mentor the principal investigator's scientific growth and development, and an advisory committee of highly regarded SCD researchers and translational scientists will provide scientific and research support. The proposed mentored training draws on the excellent SCD research and clinical resources available at the Medical College of Georgia and encompasses a prospective cohort study. This study seeks to shift clinical practice by challenging the current "as-needed" opioids strategy. Although it is known to exist, the exact incidence and prevalence of suboptimal analgesic prescribing practices in SCD patients is unknown. The absence of this information is a critical barrier to progress in optimizing analgesic therapy. This proposed study approach to addressing this critical barrier is to focus on genetic polymorphisms in cytochrome P450 genes which are known to play a role in analgesic drug metabolism and could help identify patients with higher risk for therapy failure. The study is designed to test the central hypothesis that deficient cytochrome CYP2C9, CYP2C19 and CYP2D6 metabolic phenotypes and suboptimal analgesic prescribing are positively associated with ED visits in SCD patients; and to demonstrate that CYP450 phenotypes information can be used for estimating risks for repeated ED visits for analgesic therapy failure. The Tag-It Mutation Technique is used to determine CYP450 genotypes, and the Medication Quantification Scale is used to determine suboptimal prescribing incidence. The central hypothesis if confirmed, will establish deficient CYP450 phenotypes and exposure to suboptimal prescribing as clinical risk factors. The study risk prediction rules will guide clinicians in identifying individuals who would benefit from targeted, individualized intervention to reduce risks for repeated ED visits. The study will transform current clinical practice deconstructively by demonstrating that suboptimal prescribing is common in SCD analgesic therapy. Constructively, the study will establish feasibility of CYP450 phenotyping for identifying patients likely to achieve successful analgesic relief from conventional analgesic dosing regimens or patients who might benefit from analgesic switching. PUBLIC HEALTH RELEVANCE: This project addresses pain and its management with opioid analgesics in patients with sickle cell disease. By linking suboptimal prescribing of analgesics and deficiency in inherited metabolic capacity in SCD patients to frequent utilization of acute care resources, we may identify possible risk factors for poor pharmacotherapeutic outcomes in SCD patients and validate the need for genotyping to identify at-risk SCD patients for analgesic drugs failure.